@article{HerzStefanescuLohretal.2022,
  author    = {Herz, Stefan and Stefanescu, Maria R. and Lohr, David and Vogel, Patrick and Kosmala, Aleksander and Terekhov, Maxim and Weng, Andreas M. and Grunz, Jan-Peter and Bley, Thorsten A. and Schreiber, Laura M.},
  title     = {Effects of image homogeneity on stenosis visualization at 7 T in a coronary artery phantom study: With and without B1-shimming and parallel transmission},
  series = {PloS One},
  volume    = {17},
  journal   = {PloS One},
  number    = {6},
  doi       = {10.1371/journal.pone.0270689},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300129},
  year      = {2022},
  abstract  = {Background To investigate the effects of B\(_1\)-shimming and radiofrequency (RF) parallel transmission (pTX) on the visualization and quantification of the degree of stenosis in a coronary artery phantom using 7 Tesla (7 T) magnetic resonance imaging (MRI). Methods Stenosis phantoms with different grades of stenosis (0\%, 20\%, 40\%, 60\%, 80\%, and 100\%; 5 mm inner vessel diameter) were produced using 3D printing (clear resin). Phantoms were imaged with four different concentrations of diluted Gd-DOTA representing established arterial concentrations after intravenous injection in humans. Samples were centrally positioned in a thorax phantom of 30 cm diameter filled with a custom-made liquid featuring dielectric properties of muscle tissue. MRI was performed on a 7 T whole-body system. 2D-gradient-echo sequences were acquired with an 8-channel transmit 16-channel receive (8 Tx / 16 Rx) cardiac array prototype coil with and without pTX mode. Measurements were compared to those obtained with identical scan parameters using a commercially available 1 Tx / 16 Rx single transmit coil (sTX). To assess reproducibility, measurements (n = 15) were repeated at different horizontal angles with respect to the B0-field. Results B\(_1\)-shimming and pTX markedly improved flip angle homogeneity across the thorax phantom yielding a distinctly increased signal-to-noise ratio (SNR) averaged over a whole slice relative to non-manipulated RF fields. Images without B\(_1\)-shimming showed shading artifacts due to local B\(_1\)\(^+\)-field inhomogeneities, which hampered stenosis quantification in severe cases. In contrast, B\(_1\)-shimming and pTX provided superior image homogeneity. Compared with a conventional sTX coil higher grade stenoses (60\% and 80\%) were graded significantly (p<0.01) more precise. Mild to moderate grade stenoses did not show significant differences. Overall, SNR was distinctly higher with B\(_1\)-shimming and pTX than with the conventional sTX coil (inside the stenosis phantoms 14\%, outside the phantoms 32\%). Both full and half concentration (10.2 mM and 5.1 mM) of a conventional Gd-DOTA dose for humans were equally suitable for stenosis evaluation in this phantom study. Conclusions B\(_1\)-shimming and pTX at 7 T can distinctly improve image homogeneity and therefore provide considerably more accurate MR image analysis, which is beneficial for imaging of small vessel structures.},
  language  = {en}
}
@article{RichterWechWengetal.2020,
  author    = {Richter, Julian A. J. and Wech, Tobias and Weng, Andreas M. and Stich, Manuel and Weick, Stefan and Breuer, Kathrin and Bley, Thorsten A. and K{\"o}stler, Herbert},
  title     = {Free-breathing self-gated 4D lung MRI using wave-CAIPI},
  series = {Magnetic Resonance in Medicine},
  volume    = {84},
  journal   = {Magnetic Resonance in Medicine},
  number    = {6},
  doi       = {10.1002/mrm.28383},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-218075},
  pages     = {3223 -- 3233},
  year      = {2020},
  abstract  = {Purpose The aim of this study was to compare the wave-CAIPI (controlled aliasing in parallel imaging) trajectory to the Cartesian sampling for accelerated free-breathing 4D lung MRI. Methods The wave-CAIPI k-space trajectory was implemented in a respiratory self-gated 3D spoiled gradient echo pulse sequence. Trajectory correction applying the gradient system transfer function was used, and images were reconstructed using an iterative conjugate gradient SENSE (CG SENSE) algorithm. Five healthy volunteers and one patient with squamous cell carcinoma in the lung were examined on a clinical 3T scanner, using both sampling schemes. For quantitative comparison of wave-CAIPI and standard Cartesian imaging, the normalized mutual information and the RMS error between retrospectively accelerated acquisitions and their respective references were calculated. The SNR ratios were investigated in a phantom study. Results The obtained normalized mutual information values indicate a lower information loss due to acceleration for the wave-CAIPI approach. Average normalized mutual information values of the wave-CAIPI acquisitions were 10\% higher, compared with Cartesian sampling. Furthermore, the RMS error of the wave-CAIPI technique was lower by 19\% and the SNR was higher by 14\%. Especially for short acquisition times (down to 1 minute), the undersampled Cartesian images showed an increased artifact level, compared with wave-CAIPI. Conclusion The application of the wave-CAIPI technique to 4D lung MRI reduces undersampling artifacts, in comparison to a Cartesian acquisition of the same scan time. The benefit of wave-CAIPI sampling can therefore be traded for shorter examinations, or enhancing image quality of undersampled 4D lung acquisitions, keeping the scan time constant.},
  language  = {en}
}
@unpublished{HeidenreichGassenmaierAnkenbrandetal.2021,
  author    = {Heidenreich, Julius F. and Gassenmaier, Tobias and Ankenbrand, Markus J. and Bley, Thorsten A. and Wech, Tobias},
  title     = {Self-configuring nnU-net pipeline enables fully automatic infarct segmentation in late enhancement MRI after myocardial infarction},
  edition   = {accepted version},
  doi       = {10.1016/j.ejrad.2021.109817},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323418},
  year      = {2021},
  abstract  = {Purpose To fully automatically derive quantitative parameters from late gadolinium enhancement (LGE) cardiac MR (CMR) in patients with myocardial infarction and to investigate if phase sensitive or magnitude reconstructions or a combination of both results in best segmentation accuracy. Methods In this retrospective single center study, a convolutional neural network with a U-Net architecture with a self-configuring framework ("nnU-net") was trained for segmentation of left ventricular myocardium and infarct zone in LGE-CMR. A database of 170 examinations from 78 patients with history of myocardial infarction was assembled. Separate fitting of the model was performed, using phase sensitive inversion recovery, the magnitude reconstruction or both contrasts as input channels. Manual labelling served as ground truth. In a subset of 10 patients, the performance of the trained models was evaluated and quantitatively compared by determination of the S{\o}rensen-Dice similarity coefficient (DSC) and volumes of the infarct zone compared with the manual ground truth using Pearson's r correlation and Bland-Altman analysis. Results The model achieved high similarity coefficients for myocardium and scar tissue. No significant difference was observed between using PSIR, magnitude reconstruction or both contrasts as input (PSIR and MAG; mean DSC: 0.83 ± 0.03 for myocardium and 0.72 ± 0.08 for scars). A strong correlation for volumes of infarct zone was observed between manual and model-based approach (r = 0.96), with a significant underestimation of the volumes obtained from the neural network. Conclusion The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR.},
  language  = {en}
}
@article{HeidenreichWengDonhauseretal.2019,
  author    = {Heidenreich, Julius F. and Weng, Andreas M. and Donhauser, Julian and Greiser, Andreas and Chow, Kelvin and Nordbeck, Peter and Bley, Thorsten A. and K{\"o}stler, Herbert},
  title     = {T1- and ECV-mapping in clinical routine at 3 T: differences between MOLLI, ShMOLLI and SASHA},
  series = {BMC Medical Imaging},
  volume    = {19},
  journal   = {BMC Medical Imaging},
  doi       = {10.1186/s12880-019-0362-0},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-201999},
  pages     = {59},
  year      = {2019},
  abstract  = {Background T1 mapping sequences such as MOLLI, ShMOLLI and SASHA make use of different technical approaches, bearing strengths and weaknesses. It is well known that obtained T1 relaxation times differ between the sequence techniques as well as between different hardware. Yet, T1 quantification is a promising tool for myocardial tissue characterization, disregarding the absence of established reference values. The purpose of this study was to evaluate the feasibility of native and post-contrast T1 mapping methods as well as ECV maps and its diagnostic benefits in a clinical environment when scanning patients with various cardiac diseases at 3 T. Methods Native and post-contrast T1 mapping data acquired on a 3 T full-body scanner using the three pulse sequences 5(3)3 MOLLI, ShMOLLI and SASHA in 19 patients with clinical indication for contrast enhanced MRI were compared. We analyzed global and segmental T1 relaxation times as well as respective extracellular volumes and compared the emerged differences between the used pulse sequences. Results T1 times acquired with MOLLI and ShMOLLI exhibited systematic T1 deviation compared to SASHA. Myocardial MOLLI T1 times were 19\% lower and ShMOLLI T1 times 25\% lower compared to SASHA. Native blood T1 times from MOLLI were 13\% lower than SASHA, while post-contrast MOLLI T1-times were only 5\% lower. ECV values exhibited comparably biased estimation with MOLLI and ShMOLLI compared to SASHA in good agreement with results reported in literature. Pathology-suspect segments were clearly differentiated from remote myocardium with all three sequences. Conclusion Myocardial T1 mapping yields systematically biased pre- and post-contrast T1 times depending on the applied pulse sequence. Additionally calculating ECV attenuates this bias, making MOLLI, ShMOLLI and SASHA better comparable. Therefore, myocardial T1 mapping is a powerful clinical tool for classification of soft tissue abnormalities in spite of the absence of established reference values.},
  language  = {en}
}